import unittest

from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property

from ...test_tokenization_common import TokenizerTesterMixin


lowerCAmelCase__	   =						'▁'

lowerCAmelCase__	   =						get_tests_dir('fixtures/test_sentencepiece.model')
@require_sentencepiece
@require_tokenizers
class 					snake_case	(     __snake_case							,unittest.TestCase   ):

   """simple docstring"""







   __lowerCAmelCase   						=      BigBirdTokenizer
   __lowerCAmelCase   						=      BigBirdTokenizerFast
   __lowerCAmelCase   						=      True
   __lowerCAmelCase   						=      True





   def 				snake_case__							(    self	):
     super().setUp()

     __lowercase					=		self.tokenizer_class(lowerCAmelCase_					,	keep_accents=lowerCAmelCase_	)
     tokenizer.save_pretrained(self.tmpdirname	)





   def 				snake_case__							(    self	):
     __lowercase					=		"<s>"
     __lowercase					=		1

     self.assertEqual(self.get_tokenizer()._convert_token_to_id(lowerCAmelCase_	)					,	lowerCAmelCase_	)
     self.assertEqual(self.get_tokenizer()._convert_id_to_token(lowerCAmelCase_	)					,	lowerCAmelCase_	)





   def 				snake_case__							(    self	):
     __lowercase					=		list(self.get_tokenizer().get_vocab().keys()	)

     self.assertEqual(vocab_keys[0]					,	"<unk>"	)
     self.assertEqual(vocab_keys[1]					,	"<s>"	)
     self.assertEqual(vocab_keys[-1]					,	"[MASK]"	)
     self.assertEqual(len(lowerCAmelCase_	)					,	1004	)





   def 				snake_case__							(    self	):
     self.assertEqual(self.get_tokenizer().vocab_size					,	1000	)





   def 				snake_case__							(    self	):






     if not self.test_rust_tokenizer:
       return

     __lowercase					=		self.get_tokenizer()
     __lowercase					=		self.get_rust_tokenizer()

     __lowercase					=		"I was born in 92000, and this is falsé."

     __lowercase					=		tokenizer.tokenize(lowerCAmelCase_	)
     __lowercase					=		rust_tokenizer.tokenize(lowerCAmelCase_	)
     self.assertListEqual(lowerCAmelCase_					,	lowerCAmelCase_	)

     __lowercase					=		tokenizer.encode(lowerCAmelCase_					,	add_special_tokens=lowerCAmelCase_	)
     __lowercase					=		rust_tokenizer.encode(lowerCAmelCase_					,	add_special_tokens=lowerCAmelCase_	)
     self.assertListEqual(lowerCAmelCase_					,	lowerCAmelCase_	)

     __lowercase					=		self.get_rust_tokenizer()
     __lowercase					=		tokenizer.encode(lowerCAmelCase_	)
     __lowercase					=		rust_tokenizer.encode(lowerCAmelCase_	)
     self.assertListEqual(lowerCAmelCase_					,	lowerCAmelCase_	)





   def 				snake_case__							(    self	):
     __lowercase					=		BigBirdTokenizer(lowerCAmelCase_					,	keep_accents=lowerCAmelCase_	)

     __lowercase					=		tokenizer.tokenize("This is a test"	)
     self.assertListEqual(lowerCAmelCase_					,	["▁This", "▁is", "▁a", "▁t", "est"]	)

     self.assertListEqual(
         tokenizer.convert_tokens_to_ids(lowerCAmelCase_	)					,	[285, 46, 10, 170, 382]					,	)

     __lowercase					=		tokenizer.tokenize("I was born in 92000, and this is falsé."	)
     self.assertListEqual(
         lowerCAmelCase_					,	[
             SPIECE_UNDERLINE + "I",
             SPIECE_UNDERLINE + "was",
             SPIECE_UNDERLINE + "b",
             "or",
             "n",
             SPIECE_UNDERLINE + "in",
             SPIECE_UNDERLINE + "",
             "9",
             "2",
             "0",
             "0",
             "0",
             ",",
             SPIECE_UNDERLINE + "and",
             SPIECE_UNDERLINE + "this",
             SPIECE_UNDERLINE + "is",
             SPIECE_UNDERLINE + "f",
             "al",
             "s",
             "é",
             ".",
         ]					,	)
     __lowercase					=		tokenizer.convert_tokens_to_ids(lowerCAmelCase_	)
     self.assertListEqual(
         lowerCAmelCase_					,	[8, 21, 84, 55, 24, 19, 7, 0, 602, 347, 347, 347, 3, 12, 66, 46, 72, 80, 6, 0, 4]					,	)

     __lowercase					=		tokenizer.convert_ids_to_tokens(lowerCAmelCase_	)
     self.assertListEqual(
         lowerCAmelCase_					,	[
             SPIECE_UNDERLINE + "I",
             SPIECE_UNDERLINE + "was",
             SPIECE_UNDERLINE + "b",
             "or",
             "n",
             SPIECE_UNDERLINE + "in",
             SPIECE_UNDERLINE + "",
             "<unk>",
             "2",
             "0",
             "0",
             "0",
             ",",
             SPIECE_UNDERLINE + "and",
             SPIECE_UNDERLINE + "this",
             SPIECE_UNDERLINE + "is",
             SPIECE_UNDERLINE + "f",
             "al",
             "s",
             "<unk>",
             ".",
         ]					,	)





   @cached_property
   def 				snake_case__							(    self	):
     return BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base"	)





   @slow
   def 				snake_case__							(    self	):
     __lowercase					=		"Hello World!"
     __lowercase					=		[65, 1_8536, 2260, 101, 66]

     self.assertListEqual(lowerCAmelCase_					,	self.big_tokenizer.encode(lowerCAmelCase_	)	)





   @slow
   def 				snake_case__							(    self	):
     __lowercase					=		(
         "This is a very long text with a lot of weird characters, such as: . , ~ ? ( ) \" [ ] ! : - . Also we will"
         " add words that should not exsist and be tokenized to <unk>, such as saoneuhaoesuth"
     )
     # fmt: off
     __lowercase					=		[65, 871, 419, 358, 946, 991, 2521, 452, 358, 1357, 387, 7751, 3536, 112, 985, 456, 126, 865, 938, 5400, 5734, 458, 1368, 467, 786, 2462, 5246, 1159, 633, 865, 4519, 457, 582, 852, 2557, 427, 916, 508, 405, 3_4324, 497, 391, 408, 1_1342, 1244, 385, 100, 938, 985, 456, 574, 362, 1_2597, 3200, 3129, 1172, 66]  # noqa: E231
     # fmt: on
     self.assertListEqual(lowerCAmelCase_					,	self.big_tokenizer.encode(lowerCAmelCase_	)	)





   @require_torch
   @slow
   def 				snake_case__							(    self	):
     import torch

     from transformers import BigBirdConfig, BigBirdModel

     # Build sequence
     __lowercase					=		list(self.big_tokenizer.get_vocab().keys()	)[:10]
     __lowercase					=		" ".join(lowerCAmelCase_	)
     __lowercase					=		self.big_tokenizer.encode_plus(lowerCAmelCase_					,	return_tensors="pt"					,	return_token_type_ids=lowerCAmelCase_	)
     __lowercase					=		self.big_tokenizer.batch_encode_plus(
         [sequence + " " + sequence]					,	return_tensors="pt"					,	return_token_type_ids=lowerCAmelCase_	)

     __lowercase					=		BigBirdConfig(attention_type="original_full"	)
     __lowercase					=		BigBirdModel(lowerCAmelCase_	)

     assert model.get_input_embeddings().weight.shape[0] >= self.big_tokenizer.vocab_size

     with torch.no_grad():
       model(**lowerCAmelCase_	)
       model(**lowerCAmelCase_	)





   @slow
   def 				snake_case__							(    self	):
     __lowercase					=		BigBirdTokenizer.from_pretrained("google/bigbird-roberta-base"	)
     __lowercase					=		tokenizer.decode(tokenizer("Paris is the [MASK]."	).input_ids	)

     self.assertTrue(decoded_text == "[CLS] Paris is the[MASK].[SEP]"	)





   @slow
   def 				snake_case__							(    self	):
     __lowercase					=		{"input_ids": [[65, 3_9286, 458, 3_6335, 2001, 456, 1_3073, 1_3266, 455, 113, 7746, 1741, 1_1157, 391, 1_3073, 1_3266, 455, 113, 3967, 3_5412, 113, 4936, 109, 3870, 2377, 113, 3_0084, 4_5720, 458, 134, 1_7496, 112, 503, 1_1672, 113, 118, 112, 5665, 1_3347, 3_8687, 112, 1496, 3_1389, 112, 3268, 4_7264, 134, 962, 112, 1_6377, 8035, 2_3130, 430, 1_2169, 1_5518, 2_8592, 458, 146, 4_1697, 109, 391, 1_2169, 1_5518, 1_6689, 458, 146, 4_1358, 109, 452, 726, 4034, 111, 763, 3_5412, 5082, 388, 1903, 111, 9051, 391, 2870, 4_8918, 1900, 1123, 550, 998, 112, 9586, 1_5985, 455, 391, 410, 2_2955, 3_7636, 114, 66], [65, 448, 1_7496, 419, 3663, 385, 763, 113, 2_7533, 2870, 3283, 1_3043, 1639, 2_4713, 523, 656, 2_4013, 1_8550, 2521, 517, 2_7014, 2_1244, 420, 1212, 1465, 391, 927, 4833, 388, 578, 1_1786, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [65, 484, 2169, 7687, 2_1932, 1_8146, 726, 363, 1_7032, 3391, 114, 66, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], "attention_mask": [[1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]}  # noqa: E501
     # fmt: on

     self.tokenizer_integration_test_util(
         expected_encoding=lowerCAmelCase_					,	model_name="google/bigbird-roberta-base"					,	revision="215c99f1600e06f83acce68422f2035b2b5c3510"					,	)





"""simple docstring"""



from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowercase_							=							logging.get_logger(__name__)

lowercase_							=							{
    's-JoL/Open-Llama-V1': 'https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json',
}







class    __a						( __snake_case							):
				lowerCamelCase     :       Union[str, Any]			       ='open-llama'







				def __init__( self      ,	UpperCAmelCase=10_0000      ,	UpperCAmelCase=4096      ,	UpperCAmelCase=1_1008      ,	UpperCAmelCase=32      ,	UpperCAmelCase=32      ,	UpperCAmelCase="silu"      ,	UpperCAmelCase=2048      ,	UpperCAmelCase=0.0_2      ,	UpperCAmelCase=1E-6      ,	UpperCAmelCase=True      ,	UpperCAmelCase=0      ,	UpperCAmelCase=1      ,	UpperCAmelCase=2      ,	UpperCAmelCase=False      ,	UpperCAmelCase=True      ,	UpperCAmelCase=0.1      ,	UpperCAmelCase=0.1      ,	UpperCAmelCase=True      ,	UpperCAmelCase=True      ,	UpperCAmelCase=None      ,	**UpperCAmelCase      ,	):

					'''simple docstring'''






					lowerCAmelCase_      							=			vocab_size
					lowerCAmelCase_      							=			max_position_embeddings
					lowerCAmelCase_      							=			hidden_size
					lowerCAmelCase_      							=			intermediate_size
					lowerCAmelCase_      							=			num_hidden_layers
					lowerCAmelCase_      							=			num_attention_heads
					lowerCAmelCase_      							=			hidden_act
					lowerCAmelCase_      							=			initializer_range
					lowerCAmelCase_      							=			rms_norm_eps
					lowerCAmelCase_      							=			use_cache
					lowerCAmelCase_      							=			kwargs.pop(
					    '''use_memorry_efficient_attention'''      ,	UpperCAmelCase   )
					lowerCAmelCase_      							=			hidden_dropout_prob
					lowerCAmelCase_      							=			attention_dropout_prob
					lowerCAmelCase_      							=			use_stable_embedding
					lowerCAmelCase_      							=			shared_input_output_embedding
					lowerCAmelCase_      							=			rope_scaling
					self._rope_scaling_validation()

					super().__init__(
					    pad_token_id=UpperCAmelCase      ,	bos_token_id=UpperCAmelCase      ,	eos_token_id=UpperCAmelCase      ,	tie_word_embeddings=UpperCAmelCase      ,	**UpperCAmelCase      ,	)







				def      lowerCamelCase_     ( self   ):

					'''simple docstring'''






					if self.rope_scaling is None:
						return

					if not isinstance(self.rope_scaling      ,	UpperCAmelCase   ) or len(self.rope_scaling   ) != 2:
						raise ValueError(
						    '''`rope_scaling` must be a dictionary with with two fields, `name` and `factor`, '''
						    F"""got {self.rope_scaling}"""   )
					lowerCAmelCase_      							=			self.rope_scaling.get('''type'''      ,	UpperCAmelCase   )
					lowerCAmelCase_      							=			self.rope_scaling.get('''factor'''      ,	UpperCAmelCase   )
					if rope_scaling_type is None or rope_scaling_type not in ["linear", "dynamic"]:
						raise ValueError(
						    F"""`rope_scaling`'s name field must be one of ['linear', 'dynamic'], got {rope_scaling_type}"""   )
					if rope_scaling_factor is None or not isinstance(UpperCAmelCase      ,	UpperCAmelCase   ) or rope_scaling_factor <= 1.0:
						raise ValueError(F"""`rope_scaling`'s factor field must be an float > 1, got {rope_scaling_factor}"""   )